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Topic:state estimation

State estimation is a field of research in control theory and signal processing that deals with the problem of inferring the internal state of a system based on measurements of its outputs. This involves the use of mathematical models of the system dynamics and measurement processes to estimate variables such as position, velocity, temperature, or other quantities that cannot be directly observed. State estimation techniques are commonly used in a wide range of applications, including robotics, navigation, tracking, and process control. Some common methods used in state estimation include Kalman filters, particle filters, and recursive least squares estimation.